{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ODSC RL #1",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "HjUmgGL28VkP"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from matplotlib import pyplot as plt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PgYTJF7FOeyI"
      },
      "source": [
        "import tensorflow as tf\n",
        "import tensorflow.keras as tfk"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IhO6h_Uc__Wi"
      },
      "source": [
        "# Environment"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sN_kNTX-AZ2A"
      },
      "source": [
        "class Environment:\n",
        "    '''\n",
        "        Simple environment\n",
        "    '''\n",
        "    def __init__(self, length = 100, normalize = True, noise = True, data = []):\n",
        "        self.length = length\n",
        "\n",
        "        if len(data) == 0:\n",
        "            # self.data = -pd.DataFrame(np.arange(self.length))\n",
        "            self.data = pd.DataFrame(np.sin(np.arange(length)/30.0))\n",
        "        else:\n",
        "            self.data = data\n",
        "\n",
        "        if noise:\n",
        "            self.data += pd.DataFrame(np.random.normal(0, 0.1, size=(length, )))\n",
        "\n",
        "        if normalize:\n",
        "            self.data = (self.data - self.data.min()) / (self.data.max() - self.data.min())\n",
        "\n",
        "    def get_state(self, time, lookback, diff = True):\n",
        "        window = self.data.iloc[time-lookback:time]\n",
        "        if diff: window = window.diff().fillna(0.0)\n",
        "        return window\n",
        "\n",
        "    def get_reward(self, action, action_time, reward_time, coef = 100):\n",
        "        # 0 => long; 1 => hold, 2 => short\n",
        "        if action == 0:\n",
        "            action = 1\n",
        "        elif action == 1:\n",
        "            action = 0\n",
        "        else:\n",
        "            action = -1\n",
        "        price_now = self.data.iloc[action_time]\n",
        "        price_reward = self.data.iloc[reward_time]\n",
        "        price_diff = (price_reward - price_now) / price_now\n",
        "        reward = np.sign(price_diff) * action * coef\n",
        "\n",
        "        return reward.values.tolist()[0]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zrbu-JaeKu1V"
      },
      "source": [
        "lin_env = Environment()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "3tOp5fKwKxOW",
        "outputId": "83347274-7634-4df4-972f-15a7091252e8"
      },
      "source": [
        "lin_env.get_state(10, 5, True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "        vertical-align: top;\n",
              "    }\n",
              "\n",
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              "  <thead>\n",
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              "      <th>0</th>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.019063</td>\n",
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              "    <tr>\n",
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            "text/plain": [
              "          0\n",
              "5  0.000000\n",
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              "8  0.040811\n",
              "9 -0.029573"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "T1ielGYotO3-",
        "outputId": "6e14fbc4-3c3c-4424-d07f-f772a078c7f1"
      },
      "source": [
        "plt.figure()\n",
        "plt.plot(lin_env.data)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R4CO7W5HLSb3",
        "outputId": "6d1b7341-33ec-4e6a-accf-fcfb666aedb4"
      },
      "source": [
        "lin_env.get_reward(0, 50, 51)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-100.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ch-OHZBzAlgH"
      },
      "source": [
        "# Agent"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rJQnbrkIhISN"
      },
      "source": [
        "import collections"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bzCQw17UAmRH"
      },
      "source": [
        "class BuyHoldSellAgent:\n",
        "    '''\n",
        "        A simple agent\n",
        "    '''\n",
        "    def __init__(self, state_shape = 10, action_shape = 3, experience_size = 100):\n",
        "        self.state_shape = state_shape\n",
        "        self.action_shape = action_shape\n",
        "        self.experience_size = experience_size\n",
        "        self.model = self.init_model()\n",
        "        self.experience = collections.deque(maxlen=self.experience_size)\n",
        "\n",
        "    def init_model(self):\n",
        "        inputs = tfk.Input(shape=(self.state_shape,))\n",
        "        x = tfk.layers.Dense(10, activation='relu')(inputs)\n",
        "        outputs = tfk.layers.Dense(self.action_shape, activation='linear')(x)\n",
        "        model = tfk.Model(inputs=inputs, outputs=outputs)\n",
        "        model.compile(optimizer=tfk.optimizers.Adam(0.1), loss='mse', metrics='mse')\n",
        "        return model\n",
        "\n",
        "    def save_experience(self, state_i, q_value_i, action_i, reward_i, state_i_1):\n",
        "        self.experience.append({\n",
        "            'state_i': state_i,\n",
        "            'q_value_i': q_value_i,\n",
        "            'action_i': action_i,\n",
        "            'reward_i': reward_i,\n",
        "            'state_i_1': state_i_1\n",
        "        })\n",
        "\n",
        "    def replay_experience(self, alpha, gamma, sample_size):\n",
        "        X, Y = [], []\n",
        "        indices_sampled = np.random.choice(len(self.experience), sample_size, replace=False)\n",
        "        for i, e in enumerate(self.experience):\n",
        "            if i in indices_sampled:\n",
        "                state_i, action_i, reward_i, q_value_i = e['state_i'], e['action_i'], e['reward_i'], e['q_value_i']\n",
        "                state_i_1 = e['state_i_1']\n",
        "                q_value_i_1 = self.model.predict(np.expand_dims(state_i_1, 0))[0]\n",
        "                y_i = np.zeros(self.action_shape)\n",
        "                y_i[:] = q_value_i[:]\n",
        "                y_i[action_i] = (1 - alpha) * y_i[action_i] + alpha * (reward_i + gamma * max(q_value_i_1))\n",
        "                X.append(state_i)\n",
        "                Y.append(y_i)\n",
        "        X, Y = np.array(X), np.array(Y)\n",
        "        self.model.fit(X, Y, epochs=1, batch_size=sample_size, verbose=0, shuffle=True)\n",
        "\n",
        "    def get_value_action_value(self, state):\n",
        "        pred = self.model.predict(np.expand_dims(state, 0))\n",
        "        return pred.flatten()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oS3vaStaRceW"
      },
      "source": [
        "agent = BuyHoldSellAgent()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7XUeMMlXRgiu",
        "outputId": "fce158e9-d226-498a-bd3c-f73d535db426"
      },
      "source": [
        "agent.get_value_action_value(\n",
        "    pd.DataFrame(np.array(range(10)))\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-12.582164 ,   5.6698956,   2.5076118], dtype=float32)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9OMdkUloYZ1B"
      },
      "source": [
        "# Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kru4HB2XYaeg"
      },
      "source": [
        "epochs = 5\n",
        "gamma = 0.9\n",
        "epsilon = 0.95\n",
        "alpha = 0.9"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nd9X3rnAami_"
      },
      "source": [
        "DATASET_LENGTH = 250\n",
        "WINDOW_SHAPE = 5\n",
        "REWARD_TIME = 1\n",
        "ACTIONS_SHAPE = 3\n",
        "SAMPLE_SIZE = 16"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vSzO9afGbVxb"
      },
      "source": [
        "environment = Environment(DATASET_LENGTH, True, False)\n",
        "agent = BuyHoldSellAgent(WINDOW_SHAPE, ACTIONS_SHAPE)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "31uD9MugAopP",
        "outputId": "f61a8a7a-6167-42b7-8831-51224b87ddd8"
      },
      "source": [
        "for i in range(epochs):\n",
        "\n",
        "    learning_progress = []\n",
        "    for j in range(WINDOW_SHAPE, DATASET_LENGTH - REWARD_TIME, REWARD_TIME): \n",
        "\n",
        "        # 1. getting current state\n",
        "        state_j = environment.get_state(j, WINDOW_SHAPE)\n",
        "        q_value_j = agent.get_value_action_value(state_j)\n",
        "\n",
        "        # 2. acting in this state\n",
        "        if (np.random.random() < epsilon):\n",
        "            action = np.random.randint(0, ACTIONS_SHAPE)\n",
        "        else:\n",
        "            action = (np.argmax(q_value_j))    \n",
        "\n",
        "        # 3. getting reward from this action\n",
        "        reward_value_j = environment.get_reward(action, j, j+REWARD_TIME)\n",
        "        learning_progress.append(reward_value_j)\n",
        "\n",
        "        # 4. getting next state and value there\n",
        "        state_j_1 = environment.get_state(j+1, WINDOW_SHAPE)\n",
        "\n",
        "        # 5. save this experience\n",
        "        agent.save_experience(state_j, q_value_j, action, reward_value_j, state_j_1)\n",
        "\n",
        "        if j > SAMPLE_SIZE * 2:\n",
        "            # 6. train on samples from experience\n",
        "            agent.replay_experience(alpha, gamma, SAMPLE_SIZE)\n",
        "\n",
        "    if epsilon > 0.1:\n",
        "        epsilon -= (1.0/epochs)\n",
        "\n",
        "    print('Epoch', i, '...', np.mean(learning_progress))\n",
        "    learning_progress = []"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 0 ... -3.6885245901639343\n",
            "Epoch 1 ... 12.704918032786885\n",
            "Epoch 2 ... 40.16393442622951\n",
            "Epoch 3 ... 56.967213114754095\n",
            "Epoch 4 ... 78.27868852459017\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ptLqbYzMDYMd"
      },
      "source": [
        "# Evaluation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MtgNyS5l0apF"
      },
      "source": [
        "action_to_backtest_action = {\n",
        "    0: 1,\n",
        "    1: 0,\n",
        "    2: -1\n",
        "}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WQ6rwYG6vDaD"
      },
      "source": [
        "### Same dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YKU03wEYDZaK"
      },
      "source": [
        "actions = []\n",
        "for j in range(WINDOW_SHAPE, DATASET_LENGTH, REWARD_TIME): \n",
        "    state_j = environment.get_state(j, WINDOW_SHAPE)\n",
        "    q_value_j = agent.get_value_action_value(state_j)\n",
        "    actions.append(action_to_backtest_action[np.argmax(q_value_j)])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ydfzppX4DwT4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "outputId": "477a7132-9d0b-4235-e7f7-e78cd1e576af"
      },
      "source": [
        "plt.figure(figsize = (15, 5))\n",
        "plt.plot(environment.data)\n",
        "for e, a in enumerate(actions):\n",
        "    e += WINDOW_SHAPE\n",
        "    if a == 1:\n",
        "        plt.scatter(e, environment.data.iloc[e], color = 'green')\n",
        "    elif a == -1:\n",
        "        plt.scatter(e, environment.data.iloc[e], color = 'red')\n",
        "    else:\n",
        "        pass\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hDHWBMBWzX4G",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "outputId": "e68cac8b-f305-4fcf-a7ea-738e1a3bd485"
      },
      "source": [
        "backtest = pd.DataFrame({\n",
        "    'price': environment.data.values.flatten(),\n",
        "    'signal': [0] * WINDOW_SHAPE + actions\n",
        "})\n",
        "backtest['price_diff'] = backtest['price'].diff().shift(-1)\n",
        "(backtest['price_diff'] * backtest['signal']).cumsum().plot()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd2f73d9c10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rGydYxUFvFhe"
      },
      "source": [
        "### Noisy dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LPw2wDT_hcCJ"
      },
      "source": [
        "environment2 = Environment(DATASET_LENGTH, True, True)\n",
        "actions = []\n",
        "for j in range(WINDOW_SHAPE, DATASET_LENGTH, REWARD_TIME): \n",
        "    state_j = environment2.get_state(j, WINDOW_SHAPE)\n",
        "    q_value_j = agent.get_value_action_value(state_j)\n",
        "    actions.append(action_to_backtest_action[np.argmax(q_value_j)])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "xtRiCRcwvL0j",
        "outputId": "46a74180-4fd8-423a-e9e3-9e40aa571498"
      },
      "source": [
        "plt.figure(figsize = (15, 5))\n",
        "plt.plot(environment2.data)\n",
        "for e, a in enumerate(actions):\n",
        "    e += WINDOW_SHAPE\n",
        "    if a == 1:\n",
        "        plt.scatter(e, environment2.data.iloc[e], color = 'green')\n",
        "    elif a == -1:\n",
        "        plt.scatter(e, environment2.data.iloc[e], color = 'red')\n",
        "    else:\n",
        "        pass\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "1mmWwuMdvimy",
        "outputId": "a413bd64-b666-48be-afb0-63806589f6a8"
      },
      "source": [
        "backtest = pd.DataFrame({\n",
        "    'price': environment2.data.values.flatten(),\n",
        "    'signal': [0] * WINDOW_SHAPE + actions\n",
        "})\n",
        "backtest['price_diff'] = backtest['price'].diff().shift(-1)\n",
        "(backtest['price_diff'] * backtest['signal']).cumsum().plot()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd2f7a03510>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LLQV1ShDwjS2"
      },
      "source": [
        "### Other function"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rL6-wAu0wk5J"
      },
      "source": [
        "data_new = pd.DataFrame(\n",
        "    np.cos(np.arange(DATASET_LENGTH)/5.0) + \n",
        "    np.cos(np.arange(DATASET_LENGTH)/10) + \n",
        "    np.cos(np.arange(DATASET_LENGTH)/20) + \n",
        "    np.cos(np.arange(DATASET_LENGTH)/30)\n",
        "    )"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Rz3I53Ek8Y9Q"
      },
      "source": [
        "environment3 = Environment(DATASET_LENGTH, True, True, data_new)\n",
        "actions = []\n",
        "for j in range(WINDOW_SHAPE, DATASET_LENGTH, REWARD_TIME): \n",
        "    state_j = environment3.get_state(j, WINDOW_SHAPE)\n",
        "    q_value_j = agent.get_value_action_value(state_j)\n",
        "    actions.append(action_to_backtest_action[np.argmax(q_value_j)])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "Ji3YzkKJ9CN6",
        "outputId": "ee5f733a-94a8-4106-b05f-571e41bd960c"
      },
      "source": [
        "plt.figure(figsize = (15, 5))\n",
        "plt.plot(environment3.data)\n",
        "for e, a in enumerate(actions):\n",
        "    e += WINDOW_SHAPE\n",
        "    if a == 1:\n",
        "        plt.scatter(e, environment3.data.iloc[e], color = 'green')\n",
        "    elif a == -1:\n",
        "        plt.scatter(e, environment3.data.iloc[e], color = 'red')\n",
        "    else:\n",
        "        pass\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "pnoKA7iD9CjR",
        "outputId": "f4188cc5-c1d2-45d9-ad99-ae9da74fdfb9"
      },
      "source": [
        "backtest = pd.DataFrame({\n",
        "    'price': environment3.data.values.flatten(),\n",
        "    'signal': [0] * WINDOW_SHAPE + actions\n",
        "})\n",
        "backtest['price_diff'] = backtest['price'].diff().shift(-1)\n",
        "(backtest['price_diff'] * backtest['signal']).cumsum().plot()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd35f649710>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1AQzuCcyRGU9"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5rqL2KnERNoZ"
      },
      "source": [
        "from PIL import Image\n",
        "import glob"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qqbfiogNSg1V"
      },
      "source": [
        "! rm -rf forgif\n",
        "! mkdir forgif"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "-cOmnqnWRGXc",
        "outputId": "90f61255-3770-41ca-c59a-f44d91789eab"
      },
      "source": [
        "plt.figure(figsize = (15, 5))\n",
        "plt.plot(environment3.data, color = 'black')\n",
        "for e, a in enumerate(actions):\n",
        "    e += WINDOW_SHAPE\n",
        "    if a == 1:\n",
        "        plt.scatter(e, environment3.data.iloc[e], color = 'green')\n",
        "    elif a == -1:\n",
        "        plt.scatter(e, environment3.data.iloc[e], color = 'red')\n",
        "    else:\n",
        "        pass\n",
        "    plt.savefig('./forgif/i_' + str(e).zfill(4) + '.jpg')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mu7XYyNaSJ28"
      },
      "source": [
        "frames = []\n",
        "imgs = glob.glob(\"./forgif/*.jpg\")\n",
        "frames = [Image.open(i) for i in sorted(imgs)]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r0zgHFXASL0U"
      },
      "source": [
        "# Save into a GIF file that loops forever\n",
        "frames[0].save(\n",
        "    'png_to_gif.gif', format='GIF',\n",
        "    append_images=frames[1:],\n",
        "    save_all=True,\n",
        "    duration=100, loop=0)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C7enIM7LRGaA"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}